Reconfigurable systolic arrays can be adapted to efficiently resolve a wide spectrum of computational problems; parallelism is naturally explored in systolic arrays and reconfigurability allows for redefinition of the interconnections and operations even during run time (dynamically). We present a reconfigurable systolic architecture that can be applied for the efficient treatment of several dynamic programming methods for resolving well-known problems, such as global and local sequence alignment, approximate string matching and longest common subsequence.
A great effort has been made to identify and map a large set of single nucleotide polymorphisms. The goal is to determine human DNA variants that contribute most significantly to population variation in each trait. Different algorithms and software packages, such as PolyBayes and PolyPhred, have been developed to address this problem. We present strategies to detect single nucleotide polymorphisms, using chromatogram analysis and consensi of multiple aligned sequences.